1. Field of the Invention
The invention is in the field of patient monitoring systems and methods for assessing and ensuring a level of quality and performance provided by a healthcare facility. The invention more particularly relates to ensuring that a healthcare facility is able to increase quality and performance based on patient specific attributes and needs embodied in individualized patient profiles, initiating appropriate responses to the needs based on such profiles, and refining the patient profiles based on information gathered over time for each patient.
2. Relevant Technology
Healthcare facilities provide clinical and/or wellness health care for patients and/or residents (hereinafter collectively referred to as “patients”) at such facilities. Hospitals and medical clinics provide clinical health care. Assisted living and nursing homes focus primarily on wellness health care. Most facilities provide at least some monitoring and supervision of patients to ensure they are receiving proper nutrition and medicines, are kept clean, and are protected from physical injury. A central station (e.g., a nursing station) typically functions as a primary gathering and dispatch location for caregivers. At specified intervals, or in response to a patient or resident request, a caregiver can move from the central station to a patient's location (e.g., room) and monitor or provide appropriate care.
There are often tradeoffs between ensuring that every patient at a facility receives a required level of basic care while also providing individualized care and initiating appropriate responses based on a patient's specific behaviors, attributes and needs. Even though all patients may receive the same basic level of care, some may receive too much care and others not enough care due to discrepancies between the basic standards of care and a patient's actual needs. The result is an inefficient allocation of resources that compromises the overall quality and performance of a facility and individual staff members.
There may be similar imbalances in interpreting patient behavior and fashioning appropriate responses. Not every patient behaves in the same manner, has the same health problems and issues, or requires intervention upon the occurrence of similar behaviors or events. Behavior or events that may be perfectly safe for some patients might constitute high risk to others. For example, an elderly person at a rest home who is ambulatory, requires no assistance to walk, and is known to safely walk up and down stairs without falling should not trigger caregiver intervention when approaching stairs. In contrast, caregiver intervention may be appropriate when a person who is bound to a wheel chair, who can only safely walk with assistance, or who has difficulty in perceiving or evaluating danger approaches a staircase.
One specific area of concern involves unassisted bed exiting, wheelchair exiting, wheelchair to bed transfer, or other support exiting. Unassisted support exiting by invalids or the elderly is a significant cause of injury and liability. Falls often occur due to the inability of health care facilities to provide continuous, direct supervision of patients. Unfortunately, it is typically not feasible to provide round the clock supervision of every patient due to financial and/or logistical restraints. Nevertheless, without continuous direct supervision and/or a reliable system of early notification, there may be no way for a health care provider to know when a particular patient may be engaging in support exiting or other behavior which places them at high risk for falling.
Other measurements of quality and performance involve maintaining patients within defined safety or security zones, tracking and analyzing patient gait or daily ambulation to diagnose potential injury or health issues, tracking patient contacts with assigned caregivers and/or third parties, monitoring patient socialization, initiating patient surveillance upon the occurrence of a triggering event, tracking staff movements and activities, tracking visitor movements and activities, responding to patient initiated calls or alerts, tracking assets used to provide patient care (e.g., medical devices, walkers, dentures, etc.), verifying the occurrence of prescribed treatments for each patient, and the like.
Notwithstanding the need to monitor and supervise patients to ensure an adequate level of quality and performance and prevent patient injury, the United States, Europe, Japan and other parts of the world are currently experiencing a serious shortage of nurses, nursing assistants, doctors, and other caregivers. Such shortage will only worsen with continued aging of the population. As the patient to caregiver ratio at a facility increases, the ability to provide adequate patient care and protection are likely to decrease as more patients are left unattended. There is therefore an acute need for new methods and systems that can better safeguard patients and improve the quality and performance of care delivery at a facility while also reducing facility liability, enhancing caregiver productivity, and lowering operational expenses.
Although automated patient monitoring systems have been proposed, they typically lack feasibility and have not been implemented on a wide scale. The problem with conventional patient monitoring systems is their inability to interpret and distinguish between safe or appropriate patient behaviors or conditions and those that are potentially dangerous or inappropriate as among different patients. Standard limits and alarm levels may be too tight or too loose depending on the patient. The result can be a high incidence of false positives in the case where limits and alarm levels are too tight and false negatives in the case where limits and alarm levels are too loose. A high rate of false positives can become like the boy crying wolf and might be ignored by overworked caregivers. False negatives provide no early warning of potential patient harm.
For example, one type of patient monitoring system utilizes sensors to detect patient bed exiting. A common problem that leads to a high level of false positives and false negatives is a “one size fits all” approach to detecting and interpreting patient movements. Although people often have uniquely personal ways of getting out of bed, no attempt is made in conventional monitoring systems to understand the specific movements and habits of a particular patient when bed exiting. For example, one patient might typically grasp the left handrail when commencing to bed exit while another might slide towards the foot of the bed. Persons who are left handed might exit their beds oppositely from right handed persons. Certain medical conditions might determine or alter bed exiting behavior (e.g., a person with a newly formed incision might protect against harm or pain by avoiding movements that would apply stress to the incision, even if such movements were previously used to bed exit when the patient was healthy).
In view of the foregoing, it would be an advancement in the art to provide methods and systems for monitoring patient, staff and visitor activities that can more accurately detect and interpret individual behaviors and conditions as they pertain to the overall quality and performance by a facility in delivering health care to its patients. Reducing the incidence of false positives and false negatives when detecting actionable events would be expected to increase the ability of a healthcare facility to provide an appropriate response thereto, intervene when necessary to prevent harm to a patient, and increase the overall quality and performance of the facility in providing for the specific needs of a patient as among a plurality of different patients.